- Bài trích
- Nhan đề: A transformation method for aspect-based sentiment analysis /
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Tác giả CN
| Đặng, Văn Thìn | |
Nhan đề
| A transformation method for aspect-based sentiment analysis / Đặng Văn Thìn... | |
Thông tin xuất bản
| 2018. | |
Mô tả vật lý
| tr.323-333 | |
Tóm tắt
| Along with the explosion of user reviews on the Internet, sentiment analysis has becomeone of the trending research topics in the field of natural language processing. In the last five years,many shared tasks were organized to keep track of the progress of sentiment analysis for various lan-guages. In the Fifth International Workshop on Vietnamese Language and Speech Processing (VLSP2018), the Sentiment Analysis shared task was the first evaluation campaign for the Vietnamese lan-guage. In this paper, we describe our system for this shared task. We employ a supervised learningmethod based on the Support Vector Machine classifiers combined with a variety of features. Weobtained the F1-score of 61% for both domains, which was ranked highest in the shared task. For theaspect detection subtask, our method achieved 77% and 69% in F1-score for the restaurant domainand the hotel domain respectively. | |
Thuật ngữ chủ đề
| Sentiment analysis | |
Từ khóa tự do
| Natural language processing | |
Từ khóa tự do
| Phân tích văn bản | |
Từ khóa tự do
| Aspect-based sentiment analysis | |
Từ khóa tự do
| Text analysis | |
Từ khóa tự do
| Ngôn ngữ tự nhiên | |
Từ khóa tự do
| Phân tích cảm tính | |
Tác giả(bs) CN
| Vũ, Đức Nguyên | |
Tác giả(bs) CN
| Nguyễn, Lưu Thủy Ngân | |
Tác giả(bs) CN
| Nguyễn, Văn Kiệt | |
Nguồn trích
| Tạp chí Tin học và Điều khiển học- Vol.34, No 4 |
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| 100 | 0 |aĐặng, Văn Thìn |
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| 245 | 10|aA transformation method for aspect-based sentiment analysis / |cĐặng Văn Thìn... |
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| 260 | |c2018. |
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| 300 | 10|atr.323-333 |
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| 520 | |aAlong with the explosion of user reviews on the Internet, sentiment analysis has becomeone of the trending research topics in the field of natural language processing. In the last five years,many shared tasks were organized to keep track of the progress of sentiment analysis for various lan-guages. In the Fifth International Workshop on Vietnamese Language and Speech Processing (VLSP2018), the Sentiment Analysis shared task was the first evaluation campaign for the Vietnamese lan-guage. In this paper, we describe our system for this shared task. We employ a supervised learningmethod based on the Support Vector Machine classifiers combined with a variety of features. Weobtained the F1-score of 61% for both domains, which was ranked highest in the shared task. For theaspect detection subtask, our method achieved 77% and 69% in F1-score for the restaurant domainand the hotel domain respectively. |
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| 650 | 10|aSentiment analysis |
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| 653 | 0 |aNatural language processing |
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| 653 | 0 |aPhân tích văn bản |
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| 653 | 0 |aAspect-based sentiment analysis |
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| 653 | 0 |aText analysis |
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| 653 | 0 |aNgôn ngữ tự nhiên |
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| 653 | 0 |aPhân tích cảm tính |
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| 700 | 0|aVũ, Đức Nguyên |
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| 700 | 0|aNguyễn, Lưu Thủy Ngân |
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| 700 | 0|aNguyễn, Văn Kiệt |
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| 773 | 0 |tTạp chí Tin học và Điều khiển học|gVol.34, No 4 |
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| 890 | |a0|b0|c0|d0 |
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